Multi-agent influence diagrams to hybrid threat modeling

Western governments have adopted an assortment of counter-hybrid threat measures to defend against hostile actions below the conventional military threshold. The impact of these measures is unclear because of the ambiguity of hybrid threats, their cross-domain nature, and uncertainty about how countermeasures shape adversarial behavior. This paper offers a novel approach to clarifying this impact by unifying previously bifurcating hybrid threat modeling methods through a (multi-agent) influence diagram framework. The model balances the costs of countermeasures, their ability to dissuade the adversary from executing hybrid threats, and their potential to mitigate the impact of hybrid threats. We run 1000 semi-synthetic variants of a real-world-inspired scenario simulating the strategic interaction between attacking agent A and defending agent B over a cyberattack on critical infrastructure to explore the effectiveness of a set of five different counter-hybrid threat measures. Counter-hybrid measures range from strengthening resilience and denial of the adversary’s ability to execute a hybrid threat to dissuasion through the threat of punishment. Our analysis primarily evaluates the overarching characteristics of counter-hybrid threat measures. This approach allows us to generalize the effectiveness of these measures and examine parameter impact sensitivity. In addition, we discuss policy relevance and outline future research avenues.

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Publication Details

Journal
The Journal of Defense Modeling and Simulation Applications Methodology Technology
Published
2025-03-20
DOI
https://doi.org/10.1177/15485129251315178
Primary Topic
Terrorism, Counterterrorism, and Political Violence
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-agent influence diagrams to hybrid threat modeling

Anna V. Kononova, Maarten Vonk, Thomas Bäck, Tim Sweijs
The Journal of Defense Modeling and Simulation Applications Methodology Technology
Terrorism, Counterterrorism, and Political Violence
article

Multi-agent influence diagrams to hybrid threat modeling

Anna V. Kononova, Maarten Vonk, Thomas Bäck, Tim Sweijs
article en

Abstract

Western governments have adopted an assortment of counter-hybrid threat measures to defend against hostile actions below the conventional military threshold. The impact of these measures is unclear because of the ambiguity of hybrid threats, their cross-domain nature, and uncertainty about how countermeasures shape adversarial behavior. This paper offers a novel approach to clarifying this impact by unifying previously bifurcating hybrid threat modeling methods through a (multi-agent) influence diagram framework. The model balances the costs of countermeasures, their ability to dissuade the adversary from executing hybrid threats, and their potential to mitigate the impact of hybrid threats. We run 1000 semi-synthetic variants of a real-world-inspired scenario simulating the strategic interaction between attacking agent A and defending agent B over a cyberattack on critical infrastructure to explore the effectiveness of a set of five different counter-hybrid threat measures. Counter-hybrid measures range from strengthening resilience and denial of the adversary’s ability to execute a hybrid threat to dissuasion through the threat of punishment. Our analysis primarily evaluates the overarching characteristics of counter-hybrid threat measures. This approach allows us to generalize the effectiveness of these measures and examine parameter impact sensitivity. In addition, we discuss policy relevance and outline future research avenues.

The Journal of Defense Modeling and Simulation Applications Methodology Technology
The Hague Centre for Strategic Studies (NL)
Ministerie van Buitenlandse Zaken
Openalex Percentile: Top 93%
Terrorism, Counterterrorism, and Political Violence
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Multi-agent influence diagrams to hybrid threat modeling — Anna V. Kononova, Maarten Vonk, et al. · The Journal of Defense Modeling and Simulation Applications Methodology Technology (2025) | TGRS Research Map | TGRS